110 lines
3.1 KiB
Python
110 lines
3.1 KiB
Python
import re
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import numpy as np
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import pytest
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from pandas import DataFrame, Series, date_range
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import pandas._testing as tm
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@pytest.mark.parametrize("subset", ["a", ["a"], ["a", "B"]])
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def test_duplicated_with_misspelled_column_name(subset):
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# GH 19730
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df = DataFrame({"A": [0, 0, 1], "B": [0, 0, 1], "C": [0, 0, 1]})
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msg = re.escape("Index(['a'], dtype='object')")
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with pytest.raises(KeyError, match=msg):
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df.duplicated(subset)
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@pytest.mark.slow
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def test_duplicated_do_not_fail_on_wide_dataframes():
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# gh-21524
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# Given the wide dataframe with a lot of columns
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# with different (important!) values
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data = {f"col_{i:02d}": np.random.randint(0, 1000, 30000) for i in range(100)}
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df = DataFrame(data).T
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result = df.duplicated()
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# Then duplicates produce the bool Series as a result and don't fail during
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# calculation. Actual values doesn't matter here, though usually it's all
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# False in this case
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assert isinstance(result, Series)
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assert result.dtype == np.bool_
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@pytest.mark.parametrize(
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"keep, expected",
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[
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("first", Series([False, False, True, False, True])),
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("last", Series([True, True, False, False, False])),
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(False, Series([True, True, True, False, True])),
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],
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)
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def test_duplicated_keep(keep, expected):
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df = DataFrame({"A": [0, 1, 1, 2, 0], "B": ["a", "b", "b", "c", "a"]})
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result = df.duplicated(keep=keep)
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tm.assert_series_equal(result, expected)
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@pytest.mark.xfail(reason="GH#21720; nan/None falsely considered equal")
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@pytest.mark.parametrize(
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"keep, expected",
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[
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("first", Series([False, False, True, False, True])),
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("last", Series([True, True, False, False, False])),
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(False, Series([True, True, True, False, True])),
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],
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)
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def test_duplicated_nan_none(keep, expected):
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df = DataFrame({"C": [np.nan, 3, 3, None, np.nan]}, dtype=object)
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result = df.duplicated(keep=keep)
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tm.assert_series_equal(result, expected)
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@pytest.mark.parametrize("subset", [None, ["A", "B"], "A"])
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def test_duplicated_subset(subset, keep):
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df = DataFrame(
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{
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"A": [0, 1, 1, 2, 0],
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"B": ["a", "b", "b", "c", "a"],
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"C": [np.nan, 3, 3, None, np.nan],
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}
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)
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if subset is None:
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subset = list(df.columns)
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elif isinstance(subset, str):
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# need to have a DataFrame, not a Series
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# -> select columns with singleton list, not string
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subset = [subset]
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expected = df[subset].duplicated(keep=keep)
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result = df.duplicated(keep=keep, subset=subset)
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tm.assert_series_equal(result, expected)
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def test_duplicated_on_empty_frame():
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# GH 25184
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df = DataFrame(columns=["a", "b"])
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dupes = df.duplicated("a")
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result = df[dupes]
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expected = df.copy()
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tm.assert_frame_equal(result, expected)
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def test_frame_datetime64_duplicated():
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dates = date_range("2010-07-01", end="2010-08-05")
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tst = DataFrame({"symbol": "AAA", "date": dates})
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result = tst.duplicated(["date", "symbol"])
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assert (-result).all()
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tst = DataFrame({"date": dates})
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result = tst.duplicated()
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assert (-result).all()
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